"""
量化策略组合管理系统
功能：
1. 统一加载和管理所有策略
2. 动态权重分配和调整
3. 集中风险控制
"""

import importlib
import numpy as np
from typing import Dict, List
import pandas as pd

class StrategyManager:
    def __init__(self):
        self.strategies: Dict[str, object] = {}
        self.weights: Dict[str, float] = {}
        self.risk_params = {
            'max_drawdown': 0.2,
            'volatility_target': 0.15
        }
        
    def load_strategy(self, strategy_name: str):
        """动态加载策略模块"""
        try:
            module = importlib.import_module(f'strategies.{strategy_name}')
            strategy_class = getattr(module, strategy_name.split('.')[0])
            self.strategies[strategy_name] = strategy_class()
            self.weights[strategy_name] = 1.0  # 默认权重
            print(f"成功加载策略: {strategy_name}")
        except Exception as e:
            print(f"加载策略{strategy_name}失败: {str}")

    def optimize_weights(self, 
                       returns: pd.DataFrame,
                       lookback: int = 252):
        """
        基于历史收益优化策略权重
        使用风险平价方法
        """
        cov_matrix = returns.iloc[-lookback:].cov()
        inv_vol = 1 / np.sqrt(np.diag(cov_matrix))
        weights = inv_vol / inv_vol.sum()
        
        for i, name in enumerate(self.strategies.keys()):
            self.weights[name] = weights[i]
            
    def run_all(self, market_data: dict):
        """运行所有策略并汇总信号"""
        signals = {}
        for name, strategy in self.strategies.items():
            try:
                signals[name] = strategy.generate_signal(market_data)
            except Exception as e:
                print(f"策略{name}执行失败: {str(e)}")
                signals[name] = 0
                
        # 加权汇总信号
        total_signal = sum(
            signals[name] * self.weights[name] 
            for name in signals
        )
        
        # 风险控制
        if self._check_risk(total_signal, market_data):
            return total_signal
        return 0

    def _check_risk(self, signal, market_data):
        """执行风险控制规则"""
        # 实现具体的风控逻辑
        return True

    def get_strategy_stats(self):
        """获取策略统计信息"""
        stats = []
        for name in self.strategies:
            stats.append({
                'name': name,
                'weight': self.weights[name],
                'status': 'active'
            })
        return pd.DataFrame(stats)

if __name__ == '__main__':
    # 示例用法
    manager = StrategyManager()
    
    # 加载策略
    strategies = [
        'FederatedArbitrage',
        'RLOptionMarketMaking', 
        'TransformerMultiAsset'
    ]
    for s in strategies:
        manager.load_strategy(s)
    
    # 模拟市场数据
    market_data = {
        'price': np.random.randn(100),
        'volume': np.random.randint(100, 1000, 100)
    }
    
    # 获取组合信号
    signal = manager.run_all(market_data)
    print("组合信号:", signal)
    
    # 查看策略状态
    print(manager.get_strategy_stats())